Policy enforcement using natural language processing

ABSTRACT

A term of use policy document defines permissible actions that may be implemented by a user using a computing device. A natural language processing (NLP)-based question and answer (Q&amp;A) system is trained to understand the policy document. The device includes a management application that interacts with the Q&amp;A system to identify a policy violation. When the user performs an action on the device, the application converts that action into an NLP query directed to the Q&amp;A system to determine whether the action constitutes a violation. The query may be accompanied by metadata associated with the user, the device or its state. Upon receipt of the query and any associated metadata, the Q&amp;A system determines if the user action is compliant with the policy and returns a response. Based on the response, the user&#39;s computing device may take an enforcement action, e.g., restricting or disabling functionality, or issuing a warning.

BACKGROUND OF THE INVENTION

1. Technical Field

This disclosure relates generally to information security and, inparticular, to techniques to identify when mobile device users takeactions that may violate a use policy.

2. Background of the Related Art

The recent past has seen an enormous growth in the usage andcapabilities of mobile devices, such as smartphones, tablets, and thelike. Such devices comprise fast processors, large amounts of memory,gesture-based multi-touch screens, and integrated multi-media and GPShardware chips. Many of these devices use open mobile operating systems,such as Android. The ubiquity, performance and low cost of mobiledevices have opened the door for creation of a large variety of mobileapplications.

A “term of use” policy document dictates what a user can and cannot dofrom his or her mobile device. For example, when a user connects to aWiFi hotspot, the user's Internet conduct may then be governed, at leasttheoretically, by the hotspot's (or the provider's) terms of use. Termsof use also may apply to a specific location, such as a workenvironment. For example, while on the grounds of a particular Company,the Company's terms of use may restrict the user from taking pictures,especially if such pictures may be uploaded or posted automatically tothe user's cloud-based storage, social network, or the like.

Currently, terms of use are not enforced in the physical sense orthrough any machine-implemented means; rather, it is the responsibilityof each user to honor (if at all) the terms. While theoreticallyautomation can facilitate enforcement of a “terms of use” policy, it isdifficult to apply automation processes because terms of use typicallyexist in an unstructured format; the unstructured nature of a terms ofuse policy makes it very difficult to automate any process to monitorand/or restrict user actions to comply with such terms.

BRIEF SUMMARY

A “terms of use” policy document defines one or more permissible actionsthat may be implemented by a user using a computing device (e.g., amobile phone, tablet, computer, or the like). According to thisdisclosure, a natural language processing (NLP)-based question andanswer (Q&A) system is trained to understand the policy document thatgoverns how the computing device may be used (and be consistent with thepolicy). The computing device includes a term of use policy managementapplication that interacts with the Q&A system to identify and prevent aviolation of the policy defined by the policy document. To that end,when the user performs an action on the computing device, the policymanagement application converts that action into a natural languageprocessing (NLP) query. The query is then directed to the Q&A system todetermine whether the action constitutes (or may lead to) a policyviolation. To facilitate this determination, the query may beaccompanied by (or further comprise) metadata associated with the user,the device or its state, a target of the action, or the like. Thus, inone example scenario, the user may attempt to use the device camera totake a photograph of an object within a physical location governed bythe term of use policy document. The resulting NLP query to the Q&Asystem might then be “Can the user access and use his or her camera froma mobile phone on this network?” The associated metadata might thensupply additional context information such as “Mobile phone iscloud-enabled; pictures are uploaded automatically to a third partyservice.” These query strings are merely representative. Upon receipt ofthe query and any associated metadata, the Q&A system determines if theuse action is compliant with the term of use policy document. The Q&Asystem response identifies whether the action is compliant with the termof use policy document, and the response also may include supportingevidence. The user's computing device may then take an appropriateaction, e.g., policy enforcement, restricting or disablingfunctionality, alerting or warning the user to non-compliance, or thelike.

Using this approach, an action associated with the computing device istranslated into an NLP-based policy violation query (to the Q&A system),and any associated policy enforcement is based on the NLP-based policyevaluation.

The foregoing has outlined some of the more pertinent features of theinvention. These features should be construed to be merely illustrative.Many other beneficial results can be attained by applying the disclosedinvention in a different manner or by modifying the invention as will bedescribed.

BRIEF DESCRIPTION OF THE DRAWINGS

For a more complete understanding of the present invention and theadvantages thereof, reference is now made to the following descriptionstaken in conjunction with the accompanying drawings, in which:

FIG. 1 depicts an exemplary block diagram of a distributed dataprocessing environment in which exemplary aspects of the illustrativeembodiments may be implemented;

FIG. 2 is an exemplary block diagram of a data processing system inwhich exemplary aspects of the illustrative embodiments may beimplemented;

FIG. 3 illustrates a representative mobile device in which the disclosedsubject matter may be implemented;

FIG. 4 illustrates the device of FIG. 3 interacting with a question andanswer (Q&A) system, such as a natural language processing (NLP)-basedartificial intelligence (AI) learning machine;

FIG. 5 illustrates a representative use case illustrating the basicprinciple of the natural language text processing of this disclosure;

FIG. 6 illustrates a policy management application executing in acomputing device in one embodiment; and

FIG. 7 illustrates a policy management system in which the policy engineof this disclosure may be implemented.

DETAILED DESCRIPTION OF AN ILLUSTRATIVE EMBODIMENT

With reference now to the drawings and in particular with reference toFIGS. 1-2, exemplary diagrams of data processing environments areprovided in which illustrative embodiments of the disclosure may beimplemented. It should be appreciated that FIGS. 1-2 are only exemplaryand are not intended to assert or imply any limitation with regard tothe environments in which aspects or embodiments of the disclosedsubject matter may be implemented. Many modifications to the depictedenvironments may be made without departing from the spirit and scope ofthe present invention.

Client-Server Technologies

With reference now to the drawings, FIG. 1 depicts a pictorialrepresentation of an exemplary distributed data processing system inwhich aspects of the illustrative embodiments may be implemented.Distributed data processing system 100 may include a network ofcomputers in which aspects of the illustrative embodiments may beimplemented. The distributed data processing system 100 contains atleast one network 102, which is the medium used to provide communicationlinks between various devices and computers connected together withindistributed data processing system 100. The network 102 may includeconnections, such as wire, wireless communication links, or fiber opticcables.

In the depicted example, server 104 and server 106 are connected tonetwork 102 along with storage unit 108. In addition, clients 110, 112,and 114 are also connected to network 102. These clients 110, 112, and114 may be, for example, personal computers, network computers, or thelike. In the depicted example, server 104 provides data, such as bootfiles, operating system images, and applications to the clients 110,112, and 114. Clients 110, 112, and 114 are clients to server 104 in thedepicted example. Distributed data processing system 100 may includeadditional servers, clients, and other devices not shown.

In the depicted example, distributed data processing system 100 is theInternet with network 102 representing a worldwide collection ofnetworks and gateways that use the Transmission ControlProtocol/Internet Protocol (TCP/IP) suite of protocols to communicatewith one another. At the heart of the Internet is a backbone ofhigh-speed data communication lines between major nodes or hostcomputers, consisting of thousands of commercial, governmental,educational and other computer systems that route data and messages. Ofcourse, the distributed data processing system 100 may also beimplemented to include a number of different types of networks, such asfor example, an intranet, a local area network (LAN), a wide areanetwork (WAN), or the like. As stated above, FIG. 1 is intended as anexample, not as an architectural limitation for different embodiments ofthe disclosed subject matter, and therefore, the particular elementsshown in FIG. 1 should not be considered limiting with regard to theenvironments in which the illustrative embodiments of the presentinvention may be implemented.

With reference now to FIG. 2, a block diagram of an exemplary dataprocessing system is shown in which aspects of the illustrativeembodiments may be implemented. Data processing system 200 is an exampleof a computer, such as client 110 in FIG. 1, in which computer usablecode or instructions implementing the processes for illustrativeembodiments of the disclosure may be located.

With reference now to FIG. 2, a block diagram of a data processingsystem is shown in which illustrative embodiments may be implemented.Data processing system 200 is an example of a computer, such as server104 or client 110 in FIG. 1, in which computer-usable program code orinstructions implementing the processes may be located for theillustrative embodiments. In this illustrative example, data processingsystem 200 includes communications fabric 202, which providescommunications between processor unit 204, memory 206, persistentstorage 208, communications unit 210, input/output (I/O) unit 212, anddisplay 214.

Processor unit 204 serves to execute instructions for software that maybe loaded into memory 206. Processor unit 204 may be a set of one ormore processors or may be a multi-processor core, depending on theparticular implementation. Further, processor unit 204 may beimplemented using one or more heterogeneous processor systems in which amain processor is present with secondary processors on a single chip. Asanother illustrative example, processor unit 204 may be a symmetricmulti-processor (SMP) system containing multiple processors of the sametype.

Memory 206 and persistent storage 208 are examples of storage devices. Astorage device is any piece of hardware that is capable of storinginformation either on a temporary basis and/or a permanent basis. Memory206, in these examples, may be, for example, a random access memory orany other suitable volatile or non-volatile storage device. Persistentstorage 208 may take various forms depending on the particularimplementation. For example, persistent storage 208 may contain one ormore components or devices. For example, persistent storage 208 may be ahard drive, a flash memory, a rewritable optical disk, a rewritablemagnetic tape, or some combination of the above. The media used bypersistent storage 208 also may be removable. For example, a removablehard drive may be used for persistent storage 208.

Communications unit 210, in these examples, provides for communicationswith other data processing systems or devices. In these examples,communications unit 210 is a network interface card. Communications unit210 may provide communications through the use of either or bothphysical and wireless communications links.

Input/output unit 212 allows for input and output of data with otherdevices that may be connected to data processing system 200. Forexample, input/output unit 212 may provide a connection for user inputthrough a keyboard and mouse. Further, input/output unit 212 may sendoutput to a printer. Display 214 provides a mechanism to displayinformation to a user.

Instructions for the operating system and applications or programs arelocated on persistent storage 208. These instructions may be loaded intomemory 206 for execution by processor unit 204. The processes of thedifferent embodiments may be performed by processor unit 204 usingcomputer implemented instructions, which may be located in a memory,such as memory 206. These instructions are referred to as program code,computer-usable program code, or computer-readable program code that maybe read and executed by a processor in processor unit 204. The programcode in the different embodiments may be embodied on different physicalor tangible computer-readable media, such as memory 206 or persistentstorage 208.

Program code 216 is located in a functional form on computer-readablemedia 218 that is selectively removable and may be loaded onto ortransferred to data processing system 200 for execution by processorunit 204. Program code 216 and computer-readable media 218 form computerprogram product 220 in these examples. In one example, computer-readablemedia 218 may be in a tangible form, such as, for example, an optical ormagnetic disc that is inserted or placed into a drive or other devicethat is part of persistent storage 208 for transfer onto a storagedevice, such as a hard drive that is part of persistent storage 208. Ina tangible form, computer-readable media 218 also may take the form of apersistent storage, such as a hard drive, a thumb drive, or a flashmemory that is connected to data processing system 200. The tangibleform of computer-readable media 218 is also referred to ascomputer-recordable storage media. In some instances,computer-recordable media 218 may not be removable.

Alternatively, program code 216 may be transferred to data processingsystem 200 from computer-readable media 218 through a communicationslink to communications unit 210 and/or through a connection toinput/output unit 212. The communications link and/or the connection maybe physical or wireless in the illustrative examples. Thecomputer-readable media also may take the form of non-tangible media,such as communications links or wireless transmissions containing theprogram code. The different components illustrated for data processingsystem 200 are not meant to provide architectural limitations to themanner in which different embodiments may be implemented. The differentillustrative embodiments may be implemented in a data processing systemincluding components in addition to or in place of those illustrated fordata processing system 200. Other components shown in FIG. 2 can bevaried from the illustrative examples shown. As one example, a storagedevice in data processing system 200 is any hardware apparatus that maystore data. Memory 206, persistent storage 208, and computer-readablemedia 218 are examples of storage devices in a tangible form.

In another example, a bus system may be used to implement communicationsfabric 202 and may be comprised of one or more buses, such as a systembus or an input/output bus. Of course, the bus system may be implementedusing any suitable type of architecture that provides for a transfer ofdata between different components or devices attached to the bus system.Additionally, a communications unit may include one or more devices usedto transmit and receive data, such as a modem or a network adapter.Further, a memory may be, for example, memory 206 or a cache such asfound in an interface and memory controller hub that may be present incommunications fabric 202.

Computer program code for carrying out operations of the presentinvention may be written in any combination of one or more programminglanguages, including an object-oriented programming language such asJava™, Smalltalk, C++, C#, Objective-C, or the like, and conventionalprocedural programming languages. The program code may execute entirelyon the user's computer, partly on the user's computer, as a stand-alonesoftware package, partly on the user's computer and partly on a remotecomputer, or entirely on the remote computer or server. In the latterscenario, the remote computer may be connected to the user's computerthrough any type of network, including a local area network (LAN) or awide area network (WAN), or the connection may be made to an externalcomputer (for example, through the Internet using an Internet ServiceProvider).

Those of ordinary skill in the art will appreciate that the hardware inFIGS. 1-2 may vary depending on the implementation. Other internalhardware or peripheral devices, such as flash memory, equivalentnon-volatile memory, or optical disk drives and the like, may be used inaddition to or in place of the hardware depicted in FIGS. 1-2. Also, theprocesses of the illustrative embodiments may be applied to amultiprocessor data processing system, other than the SMP systemmentioned previously, without departing from the spirit and scope of thedisclosed subject matter.

As will be seen, the techniques described herein may operate inconjunction within the standard client-server paradigm such asillustrated in FIG. 1 in which client machines communicate with anInternet-accessible Web-based portal executing on a set of one or moremachines. End users operate Internet-connectable devices (e.g., desktopcomputers, notebook computers, Internet-enabled mobile devices, or thelike) that are capable of accessing and interacting with the portal.Typically, each client or server machine is a data processing systemsuch as illustrated in FIG. 2 comprising hardware and software, andthese entities communicate with one another over a network, such as theInternet, an intranet, an extranet, a private network, or any othercommunications medium or link. A data processing system typicallyincludes one or more processors, an operating system, one or moreapplications, and one or more utilities. The applications on the dataprocessing system provide native support for Web services including,without limitation, support for HTTP, SOAP, XML, WSDL, UDDI, and WSFL,among others. Information regarding SOAP, WSDL, UDDI and WSFL isavailable from the World Wide Web Consortium (W3C), which is responsiblefor developing and maintaining these standards; further informationregarding HTTP and XML is available from Internet Engineering Task Force(IETF). Familiarity with these standards is presumed.

Mobile Device Technologies

Mobile device technologies also are well-known. A mobile device is asmartphone or tablet, such as the iPhone® or iPad®, an Android™-basedmobile device, or the like. As seen in FIG. 3, a device 300 of this typetypically comprises a CPU 302, computer memory 304, such as RAM, and adata store 306. The device software includes operating system (e.g.,Apple iOS, Android, Blackberry OS, or the like) 308, and generic supportapplications and utilities 310. Typically, the device includes aseparate graphics processing unit (GPU) 312. A touch-sensing device orinterface 314, such as a touch screen, is configured to receive inputfrom a user's touch and to send this information to processor 312. Theinterface 314 responds to gestures on the touch sensitive surface. Otherinput/output devices include software-based keyboards, cameras,microphones, and the like.

More generally, the mobile device is any wireless client device, e.g., acellphone, pager, a personal digital assistant (PDA, e.g., with GPRSNIC), a mobile computer with a smartphone client, or the like. Typicalwireless protocols are: WiFi, GSM/GPRS, CDMA or WiMax. These protocolsimplement the ISO/OSI Physical and Data Link layers (Layers 1 & 2) uponwhich a traditional networking stack is built, complete with IP, TCP,SSL/TLS and HTTP.

Thus, a mobile device as used herein is a 3G- (or next generation)compliant device that includes a subscriber identity module (SIM), whichis a smart card that carries subscriber-specific information, mobileequipment (e.g., radio and associated signal processing devices), aman-machine interface (MMI), and one or more interfaces to externaldevices. The techniques disclosed herein are not limited for use with amobile device that uses a particular access protocol. The mobile devicetypically also has support for wireless local area network (WLAN)technologies, such as Wi-Fi. WLAN is based on IEEE 802.11 standards.

Question Answering

By way of additional background, question answering (or “question andanswering,” or “Q&A”) is a type of information retrieval. Given acollection of documents (such as the World Wide Web or a localcollection), a Q&A system should be able to retrieve answers toquestions posed in natural language. Q&A is regarded as requiring morecomplex natural language processing (NLP) techniques than other types ofinformation retrieval, such as document retrieval, and it is sometimesregarded as the next step beyond search engines. Closed-domain questionanswering deals with questions under a specific domain (for example,medicine or automotive maintenance), and it can be seen as an easiertask because NLP systems can exploit domain-specific knowledgefrequently formalized in ontologies. Open-domain question answeringdeals with questions about nearly everything, and they can only rely ongeneral ontologies and world knowledge. These systems usually have muchmore data available from which to extract the answer. Systems of thistype are implemented as a computer program, executed on a machine.Typically, user interaction with such a computer program either is via asingle user-computer exchange, or a multiple turn dialog between theuser and the computer system. Such dialog can involve one or multiplemodalities (text, voice, tactile, gesture, or the like). Examples ofsuch interaction include a situation where a cell phone user is asking aquestion using voice and is receiving an answer in a combination ofvoice, text and image (e.g. a map with a textual overlay and spoken(computer generated) explanation. Another example would be a userinteracting with a video game and dismissing or accepting an answerusing machine recognizable gestures or the computer generating tactileoutput to direct the user. The challenge in building such a system is tounderstand the query, to find appropriate documents that might containthe answer, and to extract the correct answer to be delivered to theuser.

In the past, understanding the query was an open problem becausecomputers do not have human ability to understand natural language, nordo they have common sense to choose from many possible interpretationsthat elementary natural language understanding systems can produce. Asolution that addresses this problem is IBM Watson, which may bedescribed as, among other things, as an open-domain Q&A system that isan NLP artificial intelligence (AI)-based learning machine. A machine ofthis type may combine natural language processing, machine learning, andhypothesis generation and evaluation; it receives queries and providesdirect, confidence-based responses to those queries. A Q&A solution suchas IBM Watson may be cloud-based, with the Q&A function delivered“as-a-service” (SaaS) that receives NLP-based queries and returnsappropriate answers.

A representative Q&A system, such as described in U.S. Pat. No.8,275,803, provides answers to questions based on any corpus of data.The method facilitates generating a number of candidate passages fromthe corpus that answer an input query, and finds the correct resultinganswer by collecting supporting evidence from the multiple passages. Byanalyzing all retrieved passages and that passage's metadata inparallel, there is generated an output plurality of data structuresincluding candidate answers based upon the analyzing step. Then, by eachof a plurality of parallel operating modules, supporting passageretrieval operations are performed upon the set of candidate answers;for each candidate answer, the data corpus is traversed to find thosepassages having candidate answer in addition to query terms. Allcandidate answers are automatically scored causing the supportingpassages by a plurality of scoring modules, each producing a modulescore. The modules scores are processed to determine one or more queryanswers; and, a query response is generated for delivery to a user basedon the one or more query answers.

In an alternative embodiment, the Q&A system may be implemented usingIBM LanguageWare, a natural language processing technology that allowsapplications to process natural language text. LanguageWare comprises aset of Java libraries that provide various NLP functions such aslanguage identification, text segmentation and tokenization,normalization, entity and relationship extraction, and semanticanalysis.

Restricting or Disabling Device Capabilities According to “Terms of Use”Using NLP

With the above as background, the subject matter of this disclosure isnow described.

Referring to FIG. 4, the basic concept of this disclosure is shown.According to this disclosure, a computing entity (such as a mobiledevice) 402 interacts with question and answer (Q&A) system 404, such asa natural language processing (NLP)-based artificial intelligence (AI)learning machine described above. The mobile device is assumed to beoperating in a domain having at least one security policy having termsof use. A policy of this type is sometimes referred to herein as a“terms of use security policy.” Such terms may also be delineated underdifferent nomenclature, such as “acceptable use” or mere “usage policy.”The manner in which the policy is designated is not an aspect of thisdisclosure, as the described technique may be used irrespective ofnomenclature variants.

The policy includes one or more “terms of use” 405. Typically, the termsof use depend on the type and nature of the domain. Thus, the terms ofuse security policy often is domain-specific. The terms may be based onthe network to which the device is connected, the user's location (e.g.,a workplace), a user's role or responsibilities (e.g., a right to accessconfidential information), a user authentication, a user authorization,or some combination thereof. As noted above, the techniques of thisdisclosure are not limited to a particular domain or security policy, orits terms of use. The Q&A system 404 typically is located remotely fromthe domain, such as in remote location 400, although this is not alimitation or requirement. In the usual case, the Q&A system 404 isaccessible over a network, such as a wired or wireline network, a publicor private network, or the like. The mobile device interacts with theQ/A system by making queries and receiving answers. A query and itsanswer may be provided over any suitable transport, securely or in theclear. The mobile device may interact with the Q&A system using aconventional request-response protocol, programmatically, interactively,or otherwise.

Preferably, and as described above, the Q&A system 404 is based on anNLP AI-based learning machine, such as IBM Watson. The use of thedescribed machine is not a limitation, as any Q&A (or, more generally,machine learning) program, tool, device, system, or the like maycomprise system 404. Generally, and as has been described, the system404 combines natural language processing, machine learning, andhypothesis generation and evaluation; preferably, the system 404receives queries and provides direct, confidence-based responses tothose queries. The system may be cloud-based and implemented as aservice, or it may be a stand-alone functionality. Regardless of how theQ&A system is implemented, it is assumed to be capable of receivingNLP-based queries and returning answers. As used herein, a “question”and “query,” and their extensions, are used interchangeably and refer tothe same concept, namely request for information. Such requests aretypically expressed in an interrogative sentence, but they can also beexpressed in other forms, for example as a declarative sentenceproviding a description of an entity of interest (where the request forthe identification of the entity can be inferred from the context). Theparticular manner in which the Q&A system processes queries and providesresponses is not an aspect of this disclosure.

As described generally above, a “term of use” policy document definespermissible actions that may be implemented by a user using a computingdevice. The natural language processing (NLP)-based question and answer(Q&A) system 404 is trained to understand the policy document. As willbe described in more detail below, the computing device includes apolicy management application or functionality that is designed tointeract with the Q&A system 404 to identify a policy violation (or apotential policy violation). The basic technique is as follows. When theuser performs an action on the device, the policy management applicationconverts that action into an NLP query 406 directed to the Q&A system404 to determine whether the action constitutes a violation. The querymay be accompanied by metadata associated with the user, the device orits state. Upon receipt of the query and any associated metadata, theQ&A system 404 determines if the user action is compliant with thepolicy and returns a response 410. Based on the response, the user'scomputing device may take a given action, such as a policy enforcementaction. The policy enforcement action may be of any type, but typicallyis some action that restricts or disables functionality on the device toprevent what would otherwise be a policy violation. The given actionalso may be issuing a notification, such as an alert or warning (thatthe user is about to violate one of the terms of use). The notificationmay be audible, tactile or visual. The action may also involvenotification of a third party or computing entity.

FIG. 5 illustrates a process flow of a method of identifying a policyviolation according to this disclosure, using an example scenario. Inthis scenario, which is merely representative and not to be taken by wayof limitation, assume that the domain is the premises of a company atwhich the user is employed. The user's mobile device includes a camera408. Based on the user's status, it is assumed further that the terms ofuse for the domain restrict the user from taking photographs of thepremises, the facilities, or other physical resources or things. Theterms of use might be reflected in the user's employment agreement, insome corporate policy, or otherwise. The method begins at step 500 withthe Q&A system trained to understand the terms of use policy documentthat governs the user's permissible actions. This training is carriedout in a conventional manner using the Q&A system, typically in anoff-line manner. At step 502, the user performs an action on his or hercomputing device. The method then continues at step 504 to formulate theuser action on the computing device as a question using natural text. Tothis end, and as will be described in more detail below, the deviceincludes a policy management application that has the capability toperform an action-to-natural text conversion. Step 504 thus may output aquery such as “Can user access the camera from a mobile phone while onthis network?” Of course, the actual query will depend on the type ofuser action. Thus, if the user were to open a browser on the mobiledevice and attempt to retrieve some network-accessible resource, thataction may be translated to the following query: “Can user access {URL}from a mobile phone on this network. At step 506, and as an option, thepolicy management application may also obtain metadata described thedevice's state (or some other characteristic) and generate an ancillaryquery, such as “Mobile device is cloud-enabled; pictures are uploadedautomatically.” Once again, the nature of the ancillary query typicallydepends on the underlying query (that is based on the user action). Themetadata may be varied, e.g., it may comprise information associatedwith or about the user, the device or its state, a target of the action,or the like. Thus, step 506 implements a metadata-to-natural textconversion, where the metadata is data associated with the user, thedevice or the like but is otherwise distinct from the user actionitself. The steps 504 and 506 may be combined (or reversed in sequence),with the resulting query being a single composite query; in thealternative, the metadata may be associated with the main query in somenon-natural language-based manner.

At step 508, the main question and the metadata are sent to the Q&Asystem. The Q&A system processes the query at step 510 and then respondswith an answer at step 512. In particular, the Q&A system responds byindicating whether the action is compliant with the governing terms ofuse set forth in the applicable policy. The response provided at step512 may include supporting evidence, such as an applicable portion ofthe policy document. The response may be provided in a text format, in anon-text format, or otherwise. Based on the response, the method thencontinues at step 514 by taking a given action. The given action willdepend on the policy and, in particular, the terms of use, or some otherconstraint imposed. Generalizing, the action will be domain-specific.Representative actions include, without limitation, restricting afunction of the device (e.g., inhibiting the camera, blocking the accessrequest to a URL, etc.), restricting the device functionality (e.g.,permitting photographs in certain locations only), issuing an alert thatthe action is a policy violation and can subject the user to discipline,notifying a third party person or entity of the policy violation,writing a log entry in the user's personnel file, and many others.

As a skilled person will appreciate, the technique described provides amethod of formulating user actions on a mobile or other computing deviceas questions within a designated context or policy profile, inputtingsaid questions into a Q&A system wherein the knowledge corpus iscomprised of terms in a governing policy document, detectingnon-compliance of the user's action with the policy document, andwarning the user or restricting device functionality according to theterms of use. In the described embodiment, an enterprise employee is ona campus and using his or her personal mobile device, which is connectedto the enterprise network. When the employee performs actions on thephone, these actions are first checked against the enterprise's “termsof use” policy document. If the user's action is non-compliant with theenterprise's policy document, the phone may discourage or prevent theuser from taking the action.

Generalizing, it is assumed that the mobile device maintains a policycontext domain when in use. Any system features that are to be executedby the user or the device cause the issuance of a request (to the Q&Asystem) for an approval. The Q&A system utilizes a corpus of policydocuments and terms of use to check for subsequent actions, all withinthe policy context domain in which the device is operating. A responseis given, and the action is either allowed or disallowed.

FIG. 6 is a high level block diagram of the basic components of thepolicy management application 600. Typically, the application isimplemented in software as set of computer program instruction modulesor functions. The application may be integrated within the softwareoperating system (OS), with a well-defined framework for execution andquery actions, where the OS acts as a gatekeeper according to the policyprofile and context domain. In one embodiment, the policy managementapplication comprises an action-to-natural text processing engine 602, ametadata-to-natural text processing engine 604, a data store 606, acommunication interface 608, and a policy enforcement engine 610. Thesecomponents may be integrated in whole or in part, and one or morecomponents may be provided by other functionality already present in themobile device. The processing engines 602 and 604 create the queries,the communication interface 608 transmits those queries to the Q/Asystem and receives the results, and the policy enforcement engine 610enforces the applicable policy, which is stored in the data store 606.Thus, as in the example described, the user is on the Company campusconnected to the Company network on his or her mobile phone. The userthen attempts to use the camera. In one embodiment, the processingengines 602 and 604 formulate the action (of using the camera) as aquestion and include unstructured metadata: “Can I use the camera on mymobile phone while connected to the Company network? This device iscloud-enabled; pictures are automatically uploaded to a third-partyservice.” The communication interface 608 sends this unstructuredquestion and metadata to a pre-addressed Q&A system, which system may bededicated for use in the network. The Q&A system responds with arecommendation and supporting evidence; thus, e.g., the system says “No”and references a clause in the terms of use document, “Use of a cameraon a device which automatically uploads pictures to a third-partyservice is prohibited while connected to the Company network.” Based onthis response, the policy enforcement engine 610 causes the user's phoneto display a warning message “Use of the camera is not permitted on thisWiFi network.” In the alternative, the policy enforcement engine 610 maypresent use of the camera for any purpose, as has been described.

The types of user actions that may trigger a policy enforcement query tothe Q/A system may be quite varied and of course will depend on the usecase, the policy domain, the type of user, etc. Representative useractions include, without limitation, taking a picture, recording avideo, recording an audio conversation, Internet access, network accessto a particular resource, web site/page access, initiating a datatransfer, and many others.

The metadata associated with the NLP query may be quite varied, as hasbeen described. The metadata may include, without limitation, devicestate, domain characteristic, date, time, user role, deviceconfiguration data, a keyword or object associated with the user action,and many others.

It is not required that the policy enforcement take place on a mobiledevice. As noted, the natural language processing techniques of thisdisclosure may be generalized for use in any computing entity. FIG. 7illustrates a policy management system in which the workflow of thisdisclosure may be implemented. The system 700 may be implemented acrossone or more machines operating in a computing environment, such as shownin FIG. 1. Typically, the system comprises a policy administration point(PAP) 702, a policy decision point (PDP) 704, and a policy enforcementpoint (PEP) 706. Generally, the policy administration point 702 is usedto define a consent policy, which may be specified as a set of XACMLpolicy expressions. This policy uses subject attributes provided from auser repository 708, as well runtime and environment data received frompolicy information point (PIP) 710. The policy decision point (PDP) 704receives similar information and responds to an XACML policy queryreceived from the policy enforcement point (PEP) 606 to enforce thepolicy on a subject and with respect to a particular action initiated bythe subject. PEP 706 implements the desired consent workflow. In onecommercial implementation of this approach, the PAP 702 is implementedby IBM Tivoli® Security Policy Manager (TSPM) policy service or console,the PDP 704 is implemented in the TSPM runtime security service, and thePEP is implemented as a TSPM plug-in to IBM WebSphere® ApplicationServer.

The subject matter described herein has significant advantages over theprior art. Without the use of a natural text system as has beendescribed, any communication between a mobile device and an API thatdescribes permissible/compliant actions necessarily would have to behighly structured and/or rely on a standard to facilitate adoption amongall major phone carriers. In essence, the above-described processsupports a paradigm shift from communicating with what would be ahighly-structured and pre-established API, to a much more unstructuredyet highly-flexible API. By implementing such a system in this way (i.e.converting actions to unstructured questions and using a Q&A system),the architecture becomes much more flexible, allowing each phone brand(in the mobile device embodiment) to implement their own questionformulation and reactions. The only “pre-established API” is sending aquestion and receiving an answer. This flexibility provides significantadvantages.

In a variant, an employee scans a code (e.g., a QR Code) in his/hercompany's guidelines and the text for the guidelines isingested/processed directly on the device. The above-described process(using natural language text processing) can then be used to determinewhether an action (e.g. launching a camera app) might lead to aviolation of the guideline, and to display a warning along with theguideline snippet in question.

As described above, the particular enforcement action may be quitevaried. The system does not necessarily force the device to restrict orinhibit functionality. Rather, the technique presents the opportunityand mechanism by which functionality may be restricted, inhibited,subject to a warning, etc. The nature of the action may also depend onthe device or some device characteristic. For example, a Company-issuedphone may “force restriction,” while a personal device purchased by theemployee may only display a “warning.” The particular enforcement policyis beyond the scope of this disclosure.

The functionality described above may be implemented as a standaloneapproach, e.g., a software-based function executed by a processor, or itmay be available as a managed service (including as a web service via aSOAP/XML interface), in whole or in part. The particular hardware andsoftware implementation details described herein are merely forillustrative purposes are not meant to limit the scope of the describedsubject matter.

More generally, computing devices within the context of the disclosedsubject matter are each a data processing system (such as shown in FIG.2, or FIG. 3) comprising hardware and software, and these entitiescommunicate with one another over a network, such as the Internet, anintranet, an extranet, a private network, or any other communicationsmedium or link. The applications on the data processing system providenative support for Web and other known services and protocols including,without limitation, support for HTTP, FTP, SMTP, SOAP, XML, WSDL, UDDI,and WSFL, among others. Information regarding SOAP, WSDL, UDDI and WSFLis available from the World Wide Web Consortium (W3C), which isresponsible for developing and maintaining these standards; furtherinformation regarding HTTP, FTP, SMTP and XML is available from InternetEngineering Task Force (IETF). Familiarity with these known standardsand protocols is presumed.

The scheme described herein may be implemented in or in conjunction withvarious server-side architectures including simple n-tier architectures,web portals, federated systems, and the like. As noted, the techniquesherein may be practiced in a loosely-coupled server (including a“cloud”-based) environment.

Still more generally, the subject matter described herein can take theform of an entirely hardware embodiment, an entirely software embodimentor an embodiment containing both hardware and software elements. In apreferred embodiment, the functionality on each of the two sides of thevisual authentication channel is implemented in software, which includesbut is not limited to firmware, resident software, microcode, and thelike. As noted above, these functions may be integrated into otherapplications (such as webmail, document sharing, or the like), or builtinto software for this specific purpose (of facilitating the visual dataexchange channel). Furthermore, the device-specific functionality oneither side of the channel can take the form of a computer programproduct accessible from a computer-usable or computer-readable mediumproviding program code for use by or in connection with a computer orany instruction execution system. For the purposes of this description,a computer-usable or computer readable medium can be any apparatus thatcan contain or store the program for use by or in connection with theinstruction execution system, apparatus, or device. The medium can be anelectronic, magnetic, optical, electromagnetic, infrared, or asemiconductor system (or apparatus or device). Examples of acomputer-readable medium include a semiconductor or solid state memory,magnetic tape, a removable computer diskette, a random access memory(RAM), a read-only memory (ROM), a rigid magnetic disk and an opticaldisk. Current examples of optical disks include compact disk-read onlymemory (CD-ROM), compact disk-read/write (CD-R/W) and DVD. Acomputer-readable storage medium is a tangible, non-transitory item.

The computer program product may be a product having programinstructions (or program code) to implement one or more of the describedfunctions. Those instructions or code may be stored in a computerreadable storage medium in a data processing system after beingdownloaded over a network from a remote data processing system. Or,those instructions or code may be stored in a computer readable storagemedium in a server data processing system and adapted to be downloadedover a network to a remote data processing system for use in a computerreadable storage medium within the remote system.

In a representative embodiment, the device-specific components areimplemented in a special purpose computing platform, preferably insoftware executed by one or more processors. The software is maintainedin one or more data stores or memories associated with the one or moreprocessors, and the software may be implemented as one or more computerprograms. Collectively, this special-purpose hardware and softwarecomprises the functionality described above.

While the above describes a particular order of operations performed bycertain embodiments of the invention, it should be understood that suchorder is exemplary, as alternative embodiments may perform theoperations in a different order, combine certain operations, overlapcertain operations, or the like. References in the specification to agiven embodiment indicate that the embodiment described may include aparticular feature, structure, or characteristic, but every embodimentmay not necessarily include the particular feature, structure, orcharacteristic.

Finally, while given components of the system have been describedseparately, one of ordinary skill will appreciate that some of thefunctions may be combined or shared in given instructions, programsequences, code portions, and the like.

As used herein, a “client-side” application should be broadly construedto refer to an application, a page associated with that application, orsome other resource or function invoked by a client-side request to theapplication. Further, while typically the client-server interactionsoccur using HTTP, this is not a limitation either. The client serverinteraction may be formatted to conform to the Simple Object AccessProtocol (SOAP) and travel over HTTP (over the public Internet), FTP, orany other reliable transport mechanism (such as IBM® MQSeries®technologies and CORBA, for transport over an enterprise intranet) maybe used. Any application or functionality described herein may beimplemented as native code, by providing hooks into another application,by facilitating use of the mechanism as a plug-in, by linking to themechanism, and the like.

The mobile device is not limited to any particular device,configuration, or functionality. The technique may be implemented fromany computing entity, including mobile phone, tablet, television,intelligent vehicle, or other appliance.

Having described our invention, what we now claim is as follows:
 1. Amethod to identify a violation of a policy defined by a terms of usedocument that defines one or more permissible actions by a user using acomputing entity, comprising: detecting an action associated with thecomputing entity; training a natural language processing (NLP)-basedquestion and answer (Q&A) system to understand the terms of usedocument; implementing a policy management application or functionalitydesigned to interact with said natural language processing (NLP)-basedquestion and answer (Q&A) system to identify a violation of said termsof use document; converting the action using said natural languageprocessing (NLP)-based question and answer (Q&A) system by accommodatingunstructured questions such that the action is converted into a naturaltext query using a computer program executing on a hardware element;providing the natural text query for analysis to determine whether theaction constitutes a violation of the terms of use document because theaction detected is not one of the permissible actions, the determinationbeing made by a natural language comparison of the natural text queryagainst one or more terms of use that define the policy; receiving aresponse to the natural text query; and based on the response, taking apolicy enforcement action at the computing entity that limits thecomputing entity's functionality.
 2. The method as described in claim 1wherein the policy enforcement action is one of: restricting the action,inhibiting the action, issuing a notification about the action, writinga log entry about the action, and providing an indication about theaction to another entity.
 3. The method as described in claim 1 furtherincluding associating metadata with the natural text query.
 4. Themethod as described in claim 3 wherein the metadata comprises naturaltext.
 5. The method as described in claim 1 further including:converting information associated with the computing entity or a userinto metadata; converting the metadata into a natural textrepresentation; and associating the natural text query with the naturaltext representation prior to forwarding for analysis.
 6. The method asdescribed in claim 1 wherein the response to the natural text queryincludes information describing the policy violation which includesissuing an alert that the action is a policy violation, notifying athird party person or entity of the policy violation, or writing a logentry in the user's personnel file.
 7. The method as described in claim1 wherein said question and answer (Q&A) system is an open-domain Q&Asystem that is an NLP artificial intelligence (AI) based learningmachine that analyzes terms of use as part of its knowledge corpus. 8.Apparatus comprising: a processor; and computer memory holding computerprogram instructions executed by the processor to identify a violationof a policy defined by a terms of use document that defines one or morepermissible actions by a user using a computing entity, the computingentity being the apparatus, the computer program instructionscomprising: code to detect an action associated with the computingentity; code to train a natural language processing (NLP)-based questionand answer (Q&A) system to understand the terms of use document; code toimplement a policy management application or functionality designed tointeract with said natural language processing (NLP)-based question andanswer (Q&A) system to identify a violation of said terms of usedocument; code to convert the action into a natural text query; code toprovide the natural text query for analysis to determine whether theaction constitutes a policy violation of the terms of use documentbecause the action detected is not one of the permissible actions, thedetermination being made by a natural language comparison of the naturaltext query against one or more terms of use that define the policy; codeto receive a response to the natural text query; and code to take apolicy enforcement action based on the response that limits thecomputing entity's functionality.
 9. The apparatus as described in claim8 wherein the policy enforcement action is one of: restricting theaction, inhibiting the action, issuing a notification about the action,writing a log entry about the action, and providing an indication aboutthe action to another entity.
 10. The apparatus as described in claim 8wherein the computer program instructions further include code toassociate metadata with the natural text query.
 11. The apparatus asdescribed in claim 8 wherein the metadata comprises natural text. 12.The apparatus as described in claim 8 wherein the computer programinstructions further include: code to converting information associatedwith the computing entity or a user into metadata; code to convert themetadata into a natural text representation; and code to associate thenatural text query with the natural text representation prior toforwarding for analysis.
 13. The apparatus as described in claim 8wherein the response to the natural text query includes informationdescribing the policy violation.
 14. The apparatus as described in claim8 wherein the determination is made by a question and answer (Q&A)system that analyzes terms of use as part of its knowledge corpus.
 15. Acomputer program product in a non-transitory computer readable storagemedium for use in a computing entity, the computer program productholding computer program instructions which, when executed, perform amethod to prevent violation of a policy defined by a terms of usedocument that defines one or more permissible actions by a user usingthe computing entity, the computer program instructions comprising: codeto detect an action associated with the computer entity; code to train anatural language processing (NLP)-based question and answer (Q&A) systemto understand the terms of use document; code to implement a policymanagement application or functionality designed to interact with saidnatural language processing (NLP)-based question and answer (Q&A) systemto identify a violation of said terms of use document; code to convertthe action into a natural text query; code to provide the natural textquery for analysis to determine whether the action constitutes aviolation of the terms of use document because the action detected isnot one of the permissible actions, the determination being made by anatural language comparison of the natural text query against one ormore terms of use that define the policy; code to receive a response tothe natural text query; and code to take a policy enforcement actionbased on the response that limits the computing entity's functionality.16. The computer program product as described in claim 15 wherein thepolicy enforcement action is one of: restricting the action, inhibitingthe action, issuing a notification about the action, writing a log entryabout the action, and providing an indication about the action toanother entity.
 17. The computer program product as described in claim15 wherein the computer program instructions further include code toassociate metadata with the natural text query.
 18. The computer programproduct as described in claim 17 wherein the metadata comprises naturaltext.
 19. The computer program product as described in claim 15 whereinthe computer program instructions further include: code to convertinginformation associated with the computing entity or a user intometadata; code to convert the metadata into a natural textrepresentation; and code to associate the natural text query with thenatural text representation prior to forwarding for analysis.
 20. Thecomputer program product as described in claim 15 wherein the responseto the natural text query includes information describing the policyviolation.